class_docstr: Converts raw neural network output into a forecast and computes loss.
class_docstr_tok: ["Converts","raw","neural","network","output","into","a","forecast","and","computes","loss","."]
docstr: A float value that is valid for computing the loss of the
  corresponding output. By default 0.0.
docstr_tok: ["A","float","value","that","is","valid","for","computing","the","loss","of","the","corresponding","output",".","By","default","0.0","."]
code: def value_in_support(self) -> float:
      r"""
      A float value that is valid for computing the loss of the
      corresponding output. By default 0.0.
      """
      return 0.0
  
file_path: gluonts/src/gluonts/torch/distributions/output.py
imports: from typing import Callable, Dict, Optional, Tuple, Type
  import numpy
  import torch
  import torch.nn
  from gluonts.model.forecast_generator import ForecastGenerator
  from gluonts.torch.modules.lambda_layer import LambdaLayer
label_desc: Use image node_id 7 for calling the Output obj's underlying member method code with example usage: obj.value_in_support() and returns: int